A Spatially Varying Two-Sample Recombinant Coalescent, with Applications to HIV Escape Response
Abstract
Statistical evolutionary models provide an important mechanism for describing and understanding the escape response of a viral population under a particular therapy. We present a new hierarchical model that incorporates spatially varying mutation and recombination rates at the nucleotide level. It also maintains sep- arate parameters for treatment and control groups, which allows us to estimate treatment effects explicitly. We use the model to investigate the sequence evolu- tion of HIV populations exposed to a recently developed antisense gene therapy, as well as a more conventional drug therapy. The detection of biologically rele- vant and plausible signals in both therapy studies demonstrates the effectiveness of the method.
Cite
Text
Braunstein et al. "A Spatially Varying Two-Sample Recombinant Coalescent, with Applications to HIV Escape Response." Neural Information Processing Systems, 2008.Markdown
[Braunstein et al. "A Spatially Varying Two-Sample Recombinant Coalescent, with Applications to HIV Escape Response." Neural Information Processing Systems, 2008.](https://mlanthology.org/neurips/2008/braunstein2008neurips-spatially/)BibTeX
@inproceedings{braunstein2008neurips-spatially,
title = {{A Spatially Varying Two-Sample Recombinant Coalescent, with Applications to HIV Escape Response}},
author = {Braunstein, Alexander and Wei, Zhi and Jensen, Shane T. and Mcauliffe, Jon D.},
booktitle = {Neural Information Processing Systems},
year = {2008},
pages = {193-200},
url = {https://mlanthology.org/neurips/2008/braunstein2008neurips-spatially/}
}